John wrote:
I am working on a diagnostic test for an infectious disease. I am
assessing optimal cut off points within the continuous measure (which
is strongly skewed) using ROC curves, but am unclear as to whether or
not one must smooth the ROC curve prior to selecting cut off points
(my sample size is approximately 800 with 118 events, not sure if this
is important). Also, I am pretty new to Stata and am not sure how I
would go about doing this (I think this would involve log transforming
the measure and using rocfit, but beyond that I am uncertain).
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Some partial advice:
1.
ROC analysis utilize the ranks, not the absolute values of the
predictor variable, so transforming it has no consequence.
2.
ROC analysis can not tell you the "optimal cut off points" - but it
can help you decide. What is "optimal" also depends on the
consequences
of false positive and false negative conclusions.
3.
You might benefit from Roger Newson's -senspec- command. Find it by:
findit senspec
